Method and apparatus for detecting and identifying excessively vibrating blades of a turbomachine

ABSTRACT

A method and apparatus for detecting and identifying one or more excessively vibrating blades of the rotating portion of a turbomachine utilizing analysis of the characteristic Doppler waveform that results as the rotating, vibrating blade passes a fixed sensor. The acoustic energy in the vicinity of the rotating portion of the turbomachine is sensed to generate a composite electrical signal representative of the broadband acoustic spectrum. Then, through both time domain and frequency domain signal manipulations, the undesirable noise components of the composite signal are removed. The resulting signal is then displayed to reveal the characteristic Doppler waveform of the blade vibrations, which may be analyzed to indicate the location of the excessively vibrating blade as well as its relative vibration amplitude. Changes in the latter with time indicate the initiation or propagation of a blade crack.

BACKGROUND OF THE INVENTION

1. Field of the Invention

This invention relates generally to a method and apparatus for detectingand identifying excessively vibrating blades in a turbomachine and, moreparticularly, to such a method and apparatus which is employed while theturbomachine is operating.

2. Description of the Prior Art

It is generally known that turbomachinery blade failures are a majorproblem and, particularly in the steam turbine generator area, are thecause of many forced outages for U.S. electrical generating utilities.In the early stages of most blade failures, the blade will experiencecracks, which may be the result of high cycle fatigue or stresscorrosion combined with fatigue. In either event, it is undesirable andexcessive blade vibration that leads to the formation of a fatigue crackand to eventual blade failure.

High amplitude, resonant, order related blade vibration results when oneof the forcing frequencies that act on a rotating turbomachinery bladecoincides with one of the blade's many natural frequencies. In aturbine, the forcing frequencies which may cause such excessive bladevibration comprise all of the multiples of nozzle passing frequency, andall of the multiples of running speed. The former arise from the seriesof kicks that each blade receives in passing the nozzle wakes, while thelatter are due to flow non-uniformities arising from the horizontalsplit of the nozzle diaphragms and casing, internal struts, inlet orexhaust openings, nozzle plates, or the like. In each case, themultiples, or harmonics of the fundamental forcing frequency are causedby the non-sinusoidal nature of the forcing waveform. Obviously, for aconstant speed turbine, the values of all these forcing frequencies areprecisely known for each blade stage.

This is not the case, however, for the natural frequencies of thevarious blades. Here, uncertainties in the degree of fixity betweenfastener and wheel or tenon and shroud, and the necessity for empiricalestimations as to the effects of centrifugal loading, all lead touncertainties in the predicted values of the natural frequencies of theblades. in addition, normal manufacturing and assembly tolerances leadto variations from one blade to the next. Since the most predictablemodes are the lower frequency modes, and since they are also the modesmost likely to be subjected to high amplitude excitation, they are theones that manufacturers concentrate on in attempting to avoid suchresonant matches.

Actual vibration amplitudes in a resonant match of one of the forcingfrequencies with one of the natural frequencies of the blade depend onthe level of the input at the forcing frequency, on the mode shape andamplification factor of the affected mode, and on the degree of matchbetween the natural frequency and the forcing frequency. When the twofrequencies differ, the vibration occurs at the forcing frequency, notthe natural frequency. For example, in some steam turbine blade modes,amplification factors as high as 400 are not uncommon. In addition toindicating the level of increase in amplitude for an exact resonantmatch, the amplification factor indicates how the vibration amplitudevaries with the degree of match. For example, for just a 1% differencebetween the forcing frequency and the natural frequency, the vibrationamplitude drops 25% of its full resonant value for an amplificationfactor of 200, and to 12% of its full resonant value for anamplification factor of 400. Thus, although the high amplificationfactor modes are potentially more damaging, they require a more perfectfrequency match to excite them at their most damaging levels. Therefore,it is apparent that due to the previously mentioned variation in thenatural frequencies blade to blade, only a few of the blades or bladegroups in a given blade row of the rotating portion of a turbo machinemight undergo excessive, high amplitude vibration at a given time.

The extreme sensitivity to the degree of match between the forcing andnatural frequencies for high amplification factor modes has stillanother potential benefit. If a resonantly vibrating blade develops afatigue crack, it is likely that the affected natural frequency will beshifted by 1% or more. As indicated above, the accompanying reduction inamplitude should be significant and can be used as one indicator of theinitiation of a crack. Thus, a monitoring system that can measureindividual resonant blade vibrations, is also able to indicate crackinception and growth. However, the primary purpose of such a system isto detect and identify excessively vibrating blades so that such blademay be replaced before actual fatigue cracking occurs. In this manner,the turbomachine may be operated in a safer, more efficient manner whileavoiding the inconvenient and expensive outages which may result fromunanticipated turbine blade failures.

SUMMARY OF THE INVENTION

Briefly stated, the present invention provides a method and apparatusfor detecting and identifying one or more excessively vibrating bladesof the rotating portion of a turbomachine by analysis of thecharacteristic Doppler waveform as sensed by a nearby stationaryacoustic sensor. The Doppler waveform is the result of the singlefrequency acoustic energy radiated by the blades, and the changingposition and velocity of the blades relative to the sensor. The methodcomprises sensing the total acoustic energy at a fixed locationproximate the rotating portion of the turbomachine to generate acomposite electrical signal. Signal manipulations are then performedupon the composite signal in both the time domain and the frequencydomain to remove the undesirable noise generated components in order toreveal the characteristic Doppler waveform. The signal manipulationsinclude: detecting the composite signal; synchronous time averaging toremove random noise and undesirable non-order related components andblanking out the order related noise components. The resultingcharacteristic Doppler waveform is then displayed for interpretation bythe operator, or it may be additionally manipulated prior to display tofurther aid in its interpretation.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing summary, as well as the following detailed description ofthe preferred embodiments of the present invention, will be betterunderstood when read in conjunction with the accompanying drawings, inwhich:

FIG. 1 is an axial sectional view of a portion of a steam turbine;

FIG. 2 is a sectional view of the steam turbine of FIG. 1 taken alongline 2--2;

FIG. 3 is a schematic block diagram of a first method of detecting andidentifying excessively vibrating blades of a turbomachine;

FIG. 4A₁ is a graphic representation of the waveform at point A of FIG.3:

FIG. 4A₂ is a graphic representation of the frequency spectrum at pointA of FIG. 3;

FIG. 4B₁ is a graphic representation of the waveform at point B of FIG.3;

FIG. 4B₂ is a graphic representation of the frequency spectrum at pointB of FIG. 3;

FIG. 4C₁ is a graphic representation of the waveform at point C of FIG.3;

FIG. 4C₂ is a graphic representation of the frequency spectrum at pointC of FIG. 3;

FIG. 4D₁ is a graphic representation of the waveform at point D of FIG.3;

FIG. 4D₂ is a graphic representation of the frequency spectrum at pointD of FIG. 3;

FIG. 4E₁ is a graphic representation of the waveform at point E of FIG.3; and

FIG. 4E₂ is a graphic representation of the frequency spectrum at pointE of FIG. 3

FIG. 5 is a schematic block diagram of a second embodiment of thepresent invention.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

Referring to the drawings, and particularly to FIG. 1, there is shown aportion of a turbomachine, for example, a steam turbine 10. The steamturbine 10 is of a type generally well known in the art and a detailedexplanation of all of its structure and operation is not necessary for acomplete understanding of the present invention. Suffice it to say thata pressurized operating fluid, in this case steam, is introduced intothe left or upstream end of the generally cylindrical turbine casing 11from a convenient source, for example, a coil or oil fired boiler. Thesteam flows to the right or axially downstream over a plurality ofgenerally radially directed circumferentially distributed guide vanes ornozzles 12 which terminate in a ring 13 and are arranged to concentrateand properly orient the steam flow. The concentrated and properlyoriented steam then flows over a plurality of generally outwardlyradially extending buckets or turbine blades 14 which are attachedthrough a suitable rotor disk 16 to a centrally located axially rotatingturbine shaft 18. As the steam passes through the aerodynamically shapedturbine blades 14, energy is removed from the steam and is impartedthrough the blades to drive the shaft 18 into rotation. The steam maythen pass downstream to subsequent stages of nozzles and blades (notshown) where additional energy may be removed from the steam andimparted to the rotating shaft 18. The rotating turbine shaft 18 may beemployed to do useful work, for example, by driving an electricgenerator unit (not shown).

As discussed in detail above, in a turbomachine like the steam turbine10, there are significant operational and maintenance problems caused byexcessive vibration of the blades 14. The present invention involves amethod for pinpointing the specific individual blades of an operatingturbomachine that are vibrating excessively, utilizing the acousticenergy radiated by the vibrations of the blades as determined by a fixeddynamic pressure transducer or sensor 20. The sensor 20 may be mountedin the turbine casing 11 slightly downstream from the rotating blades14.

It is generally known that any rotating turbomachinery blade that isvibrating excessively will radiate acoustic energy into the surroundingfluid environment at the frequency of its vibration. If the radiatedenergy is to be detected by a relatively fixed or stationary sensor 20and if the energy radiating blade is simultaneously rotating such thatit has a velocity component along a line joining the moving blade andthe fixed sensor 20, then the frequency of the energy radiated from theblade as detected by the sensor 20 will be altered from the frequencyactually radiated from the blade. This concept is known as moving sourceDoppler and the new frequency as detected by the sensor is given by thefollowing formula:

    f'=f(V+w)/(V+w-v)                                          (1)

where

f is the frequency of the radiating source or vibrating blade;

f' is the frequency detected by the sensor;

v is the instantaneous velocity of the blade toward the fixed sensoralong a line joining the blade and the sensor;

w is the average velocity of the surrounding operational fluid movingtoward the fixed sensor along a line joining the blade and the sensor;and

V is the velocity of sound in the operating fluid.

In order clearly to illustrate the principle behind the moving sourceDoppler method, suitable reference marks A-F have been placed at variouspositions around the turbine 10 as shown on FIG. 2. When, during itsrotation, a single excessively vibrating blade is instantaneouslylocated at position A, the vibrating blade is at its greatest distancefrom the sensor 20. Since the amplitude of the acoustic energy radiatedfrom the vibrating blade which arrives at the sensor 20 is inverselyrelated to the distance between the sensor 20 and the vibrating blade,the amplitude of the acoustic energy detected by the sensor 20 from thevibrating blade is at its lowest level when the vibrating blade isinstantaneously located at position A. In addition, since at position Athe instantaneous velocity component of the vibrating blade toward thesensor 20 (v in the above equation) is zero, the frequency of theacoustic energy as detected by the sensor 20 is the same as the actualfrequency of the vibrating blade.

As the vibrating blade moves around to position B, the blade is closerto the sensor 20 and has a significant instantaneous velocity componenttoward the sensor 20. Thus, both the amplitude and the frequency of theenergy radiated from the blade as detected by the sensor 20 aresubstantially increased.

When the vibrating blade reaches position C, it is closer yet to thesensor 20 and its instantaneous velocity component toward the sensor 20is at its maximum. Thus, at position C, the amplitude of the energyradiated from the vibrating blade as received by the sensor 20 isincreased and the frequency of the radiated energy as detected by thesensor 20 is at its maximum.

At position D, the vibrating blade is instantaneously at its closestdistance to the sensor 20 so the amplitude of the radiated energyreceived by the sensor 20 from the vibrating blade is at its maximumvalue. However, since there is no instantaneous velocity component ofthe vibrating blade in the direction toward the sensor 20, the frequencyof the blade vibrations as detected by the sensor 20 is the actualfrequency of the vibrating blade.

As the vibrating blade reaches position E, the distance from the sensor20 and thus the amplitude of the energy received by the sensor 20 is thesame as it was at position C. However, since the instantaneous velocitycomponent of the blade is at its maximum in a direction away from thesensor 20, the frequency detected by the sensor 20 is at its minimum.

At position F, the amplitude of the energy received by the sensor 20 isthe same as it was at position B but the negative instantaneous velocitycomponent of the blade results in the frequency detected by the sensor20 being below the actual blade vibrating frequency.

In summary, as the vibrating blade approaches the sensor 20, both itsfrequency and amplitude appear to increase. After passing the sensor,its frequency appears to decrease sharply and its amplitude appears todecrease slowly as it moves away. By starting at a known rotor position(in a manner as described in detail below) and using suitable samplingtechniques, a characteristic Doppler waveform (which is repeated exactlythe same for each revolution of the turbine shaft 18) indicating theamplitude and frequency variations may be plotted as a function of time,and from the Doppler waveform, the location of the excessively vibratingblade can easily be determined. This technique may still be applicableto blades which are rotating at speeds in excess of the speed of soundin the operating medium, for example gas turbine engine compressors,when as seen by formula 1 above, the speed of the rotating blade stilldoes not exceed the effective speed of sound (V+w).

Although the above-described method in theory is a useful way ofdetecting and identifying one or more excessively vibratingturbomachinery blades, in a real world environment, additionalacoustical signals inherent in the operation of the turbine 10 come intoplay to form a composite signal which tends to mask the charateristicDoppler waveform and to severely complicate the method. For example, therush of the fluid medium (in this embodiment, steam) around the sensor20 and the adjacent turbine casing results in the generation of asignificant, broadband random noise signal which may be an order ofmagnitude greater in amplitude than the Doppler signal from theexcessively vibrating blades. In addition, order related signals, suchas blade passing frequency, running speed, etc., and their harmonics,may also be an order of magnitude greater than the Doppler signal. Theadditional acoustical signals, all of which are also detected by thesensor 20, tend to mask or drown out the desired Doppler signal. Thepresent invention involves a straightforward method for manipulating theoutput signal from the sensor 20 in order to circumvent theabove-discussed real world operational problems involved in employingthe moving source Doppler technique to detect and identify one or moreexcessively vibrating turbine blades.

The method of the present invention may be best understood by settingforth an illustrated example. For the purposes of the example, theturbine 10 is assumed to comprise 64 nozzles and 67 blades, each bladehaving an effective radius of 0.762 m (30 inches). The turbine shaft 18is assumed to be rotating at a constant 3000 rpm, thereby establishingthe circumferential velocity of the blades 14 at 239.4 meters/second(9,425 inches/second). The radius of the turbine casing at the locationof the sensor 20 is 0.838 meters (33 inches). The velocity of sound inthe steam is assumed to be 381 m/s (15,000 in/s), and, since theabsolute velocity of the steam leaving the blades 14 is mostly axial,the steam serves to increase the effective sound velocity only when avibrating blade is near the sensor 20. For simplicity, this is neglectedin the ensuing discussion.

It is also assumed that three of the blades 14 are vibrating excessivelyat the nozzle passing frequency 3,200 Hz, and for simplicity, all threeblades are vibrating at the same amplitude. It is further assumed thatthe first of the excessively vibrating blades is located at a position90° behind the sensor 20 (at position B of FIG. 2) at the beginning ofthe record and that the second and third excessively vibrating bladesare located 8 and 17 blades respectively behind the first blade.

Referring now to FIG. 3, there is shown a functional block diagram ofthe method of the present invention. The first step shown in functionalblock 30 is the sensing of the composite acoustical signals at a singlefixed location slightly downstream from the turbine stage, for example,by sensor 20. FIG. 4A₁ shows the single revolution waveform at point Aof FIG. 3 resulting from the sensing of the aggregate acoustical signal.It is clear from FIG. 4A₁ that no characteristic Doppler waveform isreadily discernable. FIG. 4A₂ is a representation of the correspondingfrequency spectrum of the single revolution waveform signal at point Aof FIG. 3. As expected, the broadbanded frequency spectrum in this formis not particularly helpful in detecting or identifying the threeexcessively vibrating turbine blades.

The random steam flow noise component may be substantially reduced fromthe sensed acoustic signal at point A of FIG. 3 through the applicationof the known procedure of synchronous time domain averaging as shown infunctional block 32. A once per revolution phase reference signal isgenerated (as shown in functional block 34 of FIG. 3) and is utilized inthe time domain averaging procedure. The phase reference signal may beaccomplished by known sensing methods. For example, a fixed fiberopticalprobe (not shown) may be employed to sense the passing of a smallreflective tape segment located at a fixed position on the turbine shaft18. The phase reference sensing results in the generation of a pulseeach time the same portion of the turbine shaft 18 passes by the probe,thereby establishing the passing of a fixed known blade position.

The phase reference pulses are employed in the synchronous timeaveraging process to indicate the beginning of each revolution of theturbine shaft 18 and the beginning of each sampling process. The numberof samples in a record may be any value, but it is usually some power oftwo. 512 samples per record are assumed for this example. Additionally,the sampling interval or time spacing between each of the 512 samplesmay be any fixed value; however, it is preferred to have the samplinginterval such that all 512 samples comprise exactly one revolution. Thisis accomplished by frequency multiplying the phase reference signal by512 (functional block 36), the resultant signal serving as the samplingclock. Of course, the waveform must be low pass filtered at less thanhalf this sampling rate prior to its being sampled to prevent aliasing.The synchronous time domain averaging process involves a repetition ofsampled records, each starting at the phase reference, with thecorresponding sampled points of each then added algebraically anddivided by the total number of averages. The result is that any signalwhich is not repeated at the exact same point in the rotational cycleeventually averages to zero. Obviously, the random steam flow noise aswell as any other random or non-synchronous noise signals fall into thiscategory. The repetitive Doppler waveform from any blades that arevibrating excessively at some multiple of running speed, as well as anyother order related signals remain undiminished by the time domainaveraging process. It will be appreciated that the length of time thatthe time domain averaging process is continued may vary depending uponthe relative amplitudes of the random noise signals to the desirableDoppler waveform signals. Obviously, the longer the time averaging iscontinued, the less significant the random noise signals become. In thecase of a turbine operating at 3000 rpm, up to 10,000 averages could becompleted in less than seven minutes.

A representation of the single revolution waveform at point B of FIG. 3resulting after significant synchronous time domain averaging is shownon FIG. 4B₁. As shown, although the synchronous time averaging processis effective in removing the random noise, the resulting signal is stillinsufficient to reveal the needed information regarding the excessivelyvibrating blades.

FIG. 4B₂ shows the corresponding frequency spectrum. Even though onlythe magnitude is shown in FIG. 4B₂, the frequency spectrum actuallyincludes both magnitude and phase information because of the knownstarting position as established with the phase reference sensing offunctional block 34. Thus, it is possible to go back and forth betweenthe frequency domain and the time domain at will in order to performsignal manipulations in either domain.

FIG. 4B₂ shows the characteristic Doppler spectrum of the waveform ofFIG. 4B₁, but gives no clear indication of how many turbine blades maybe vibrating excessively or in what positions the vibrating blades maybe located. In fact, it shows no clear evidence of Doppler at all. Theproblem, of course, relates to the presence of a few large discretecomponents, clearly visible in the spectrum. The largest component at3,350 Hz is the blade passing component, and it clearly dominates thescene. Also included are large components at running speed, and the 2ndand 3rd harmonics of running speed, 50 Hz, 100 Hz and 150 Hz. These areevidenced in the general up and down movement of the waveform.

All of these signal components are order related or repetitive on arotational basis and therefore are not removable through synchronoustime averaging. However, they can be conveniently removed, or blanked,directly from the complex frequency spectrum utilizing blankingtechniques which are well known to those skilled in the art. Then theblanked or modified spectrum can be inverse transformed back into thetime domain, and the Doppler waveform should become apparent. Thesecomponents can be either completely blanked (replaced with zeroes), orthe real and imaginary values of the affected spectral points can bereplaced with interpolated values. It is the latter technique that hasbeen employed in the order related noise blanking functional box 38 ofFIG. 3 used here to modify the spectrum of FIG. 4B₂.

FIG. 4C₂ shows the modified spectrum at point C of FIG. 3 and FIG. 4C₁shows the corresponding modified reconstructed time waveform obtained byinverse transforming of the modified spectrum of FIG. 4C₂. The threeDoppler signatures that were buried in the original time waveforms ofFIG. 4A₁ and 4B₁ are now readily apparent, with no shifting in the timedomain occurring from the frequency domain blanking and inversetransform procedure. Thus, the capability of locating the threeexcessively vibrating blades remains unimpaired despite the frequencyblanking process.

The essence of the technique should now be clear. The Doppler mechanismtransforms the single frequency of the vibrating blades into a broadbandmulti-frequency function which contains information as to the locationof the vibrating blades. Like the original frequency, all the newfrequencies are order related since the waveform retains itsrotationally repetitive nature in the time domain. Thus, it is at oncepossible to use synchronous time domain averaging to remove thenon-rotational masking effects, and to use discrete frequency blankingto remove the order related masking effects, the latter process hardlydistorting the desired signal since the information in the Dopplersignature is spread so broadly in the frequency domain.

A key feature of the present invention is its ability to identify thelocation of the excessively vibrating blades. Thus, the object is toknow exactly when the vibrating blade is directly beneath the sensor.This does not coincide with the maximum frequency point or with theminimum frequency point, each of which is difficult to ascertain fromthe waveform anyway. Rather, it coincides with the maximum of theamplitude envelope of the waveform, corrected by the time it takes forsound to travel to the sensor from a blade directly beneath it (seeformula 1 above). In this example, this correction time is 0.0762 (3in.) divided by 381 m/s, (15,000 in/s), or 0.20 ms.

The amplitude envelope of the waveform may be developed, as shown inFIG. 4D₁, by first detecting (functional block 40 of FIG. 3) or makingpositive all of the negative going peaks of the waveform of FIG. 4C₁.Detecting may be accomplished as above or by other suitable techniquessuch as squaring each point. Detecting has the dual effect of shiftingthe frequency of the original Doppler signature upward, while adding ina new frequency band as shown in the corresponding frequency spectrum of4D₂.

Next, all of the frequency components above 1965 Hz (the originalDoppler minimum frequency as predicted by formula 1 above) of thefrequency spectrum of FIG. 4D₂ are blanked to zero as shown infunctional box 42, leaving just the low frequency portion of thespectrum as shown in FIG. 4E₂ (representing the frequency spectrum atpoint E of FIG. 3). Reconstruction (inverse transforming) of the lowfrequency spectrum portion of FIG. 4E₂ then yields the corresponding newtime waveform of FIG. 4E₁. The enhanced time waveform of FIG. 4E₁ isproportional to and synchronized with the envelope of the originalDoppler waveform.

The resulting waveform of FIG. 4E₁ is then displayed (functional block44 of FIG. 3) for purposes of analysis by an operator. As shown in sucha display, the three time markers of FIG. 4E₁, at 5.20 ms, 7.59 ms, and10.27 ms (with 0.20 ms added for the travel time correction), correspondto the times from the beginning of the record (when the phase referencepulse appears) that the three excessively vibrating blades pass beneaththe sensor 20. Recall that the resolution from one blade to the next is0.30 ms in this example. Thus, the enhanced characteristic Dopplerwaveform detects the vibrating blades, indicates their relativevibration level and pinpoints their location. The displayed signal maybe analyzed over a period of time to determine changes in the relativeamplitude of a blade's vibration. As discussed above, the changes areindicative of the initiation or propagation of a blade crack.

The above-described method may be employed to detect and identifyexcessively vibrating turbomachinery blades in cases in which thevibrations are order related. For example, the above-described methodmay be employed to detect and identify such vibrating blades where thevibrations are caused by nozzle passing frequency, running speed, or anyharmonics thereof. However, the above-described method is not effectivein detecting and identifying such vibrating blades where the vibrationsare non-order related. For example, self-excited vibration of a turbineblade at its own natural frequency independent of the running speed orflutter is such a non-order related vibration which may not be detectedby the above-described method. Although the single sensor 20 detects thenon-order related vibrations as well as the order related vibrations,the subsequent signal manipulation steps as described above areestablished to isolate the order related vibrations and to eliminatenon-order related signals. Accordingly, to employ the moving sourceDoppler technique for the detection and identification of excessivenon-order related vibrations in the blades, it is necessary to slightlymodify the above-described method of manipulating the signal from thesensor.

FIG. 5 shows another embodiment of the present invention which may beemployed for the detection and identification of either order related ornon-order related vibrations in rotating turbomachinery blades. Themethod makes use of the fact that the envelope of the Doppler waveformis order related even though the waveform itself may not be. The signalmanipulation steps of the method of FIG. 5 are substantially the same asthose of the above-described method as shown in FIG. 3, except that theorder of the steps is slightly rearranged. Accordingly, the functionalblocks of FIG. 5 will be identified using the same reference numerals aswere used on FIG. 3 with the addition of primes thereto.

As mentioned above, in the embodiment of FIG. 5, the dynamic pressuresensing 30' phase reference sensing 34' and frequency multiplying 36'operations, as well as the sampling rate, are exactly the same as thecorresponding operations of the embodiment of FIG. 3. However, in theFIG. 5 embodiment, the signal from the dynamic pressure sensing 30' arefirst passed through a detecting operation 40' wherein the signals areessentially full wave rectified. In this manner, the subsequentsynchronous time averaging operation 32' averages the Doppler waveformto the mean value of its envelope and the random noise to a D.C. value(rather than to zero as is done in the embodiment of FIG. 3).

The detected and envelope time averaged signal is then passed to theorder related noise blanking operation 38' wherein, operating in thefrequency domain as described above, the undesirable, now doubled, orderrelated components of the signal (i.e., blade passing component), aswell as the D.C. component resulting from the time averaging of therandom noise components, are blanked out of the signal.

An inverse transformation or reconstruction of the frequency domainsignal remaining after the order related noise blanking operation 38'yields a time domain waveform which, in the case of non-order relatedvibrations, will be similar to the waveform of FIG. 4E₁. Thus, as shownby line 50', in the case of non-order related vibrations, the timedomain waveform may be directly displayed and interpreted to determinethe location of the excessively vibrating blades.

In the case of order related vibrations, a reconstruction of thefrequency domain signal remaining after the order related noise blankingoperation 38' yields a time domain waveform which is similar to thewaveform of FIG. 4D₁. As discussed above in relation to the embodimentof FIG. 3, it is necessary to blank out the high frequency components ofthe signal in order to obtain a clear resolution of the waveform. Thisis accomplished, in the case of order related vibrations, by theblanking of high frequency portion operation as shown in functionalblock 42'. An inverse transformation of the signal remaining after thehigh frequency blanking operation results in a time domain waveformsimilar to that of FIG. 4E₁ which may then be displayed and interpreted.

From the foregoing description, it can be seen that the presentinvention comprises a method and apparatus for detecting and identifyingexcessively vibrating turbomachinery blades which is relatively simpleto employ and requires only a single stationary sensor for each rotatingblade stage. It will be recognized by those skilled in the art thatchanges or modifications may be made to the above-described embodimentswithout departing from the broad inventive concepts of the invention. Itis understood, therefore, that this invention is not limited to theparticular embodiments disclosed, but it is intended to cover allmodifications which are within the scope and spirit of the invention asdefined by the appended claims.

I claim:
 1. A method for detecting and identifying an excessivelyvibrating blade of the rotating portion of a turbomachine by analysis ofthe characteristic Doppler waveform resulting from the vibrating bladecomprising the steps of:sensing the acoustic energy at a fixed locationproximate the rotating portion of the turbomachine to generate acomposite electrical signal; synchronous time averaging the compositesignal to remove random noise and non-order related componentstherefrom; blanking out the order related noise components of thesynchronous time averaged signal to reveal the characteristic Dopplerwaveform of the vibrating blade; and displaying the resultingcharacteristic Doppler waveform to indicate the location of theexcessively vibrating blade and its relative vibration amplitude.
 2. Themethod as recited in claim 1 further including the step of envelopedetecting the blanked, synchronous time averaged signal to enhance theamplitude envelope prior to displaying the resulting waveform.
 3. Amethod for detecting and identifying an excessively vibrating blade ofthe rotating portion of a turbomachine by analysis of the characteristicDoppler waveform resulting from the vibrating blade comprising the stepsof:sensing the acoustical energy at a fixed location proximate therotating portion to generate a composite electrical signal; sensing thephase of the rotating portion to generate a phase reference signalrepresentative of the time when a predetermined location on the rotatingportion passes a fixed location; sampling the composite signal andsynchronously time averaging at least two time records of the sampledcomposite signal utilizing the phase reference signal as an initiationtrigger; blanking out the order related noise from the synchronous timeaveraged signal to reveal the characteristic Doppler waveform resultingfrom the vibrating blade; detecting the blanked signal; blanking out thehigh frequency portion of the detected signal to enhance the amplitudeenvelope; and displaying the resulting enhanced signal to pinpoint thelocation of the vibrating blade and indicate its relative vibrationamplitude.
 4. The method as recited in claim 3 further including thestep of establishing a sampling rate so that the number of samples ineach time record multipled by the sampling rate exactly matches onerevolution of the rotation portion.
 5. A method for detecting andidentifying an excessively vibrating blade of the rotating portion of aturbomachine by analysis of the characteristic Doppler waveformresulting from the vibrating blade comprising the steps of:sensing theacoustic energy at a fixed location proximate the rotating portion ofthe turbomachine to generate a composite electrical signal; detectingthe composite signal; synchronous time averaging the detected compositesignal to remove random noise and undesirable non-order relatedcomponents therefrom; blanking out the order related noise components ofthe synchronous time averaged signal; and displaying the resultingsignal to reveal the characteristic Doppler waveform of the vibratingblade, or its envelope to pinpoint the location of the excessivelyvibrating blade and indicate its relative vibration amplitude.
 6. Themethod as recited in claim 5 further including the step of blanking outthe high frequency portion of the blanked synchronous time averagedsignal prior to displaying the resulting signal.
 7. The method asrecited in claims 1, 2, 3 or 5, further including the step of analyzingthe displayed signal over a period of time to determine changes in therelative amplitude which indicate the initiation or propagation of ablade crack.
 8. An apparatus for detecting and identifying anexcessively vibrating blade of the rotating portion of a turbomachine byanalysis of the characteristic Doppler waveform resulting from thevibrating blade comprising:sensor means disposed at a fixed locationproximate the rotating portion of the turbomachine for sensing theacoustical energy and generating a composite electrical signal inresponse thereto; detecting means for detecting the composite signal;time averaging means for synchronous time averaging the detectedcomposite signal to remove random noise and undesirable non-orderrelated components therefrom; blanking means for blanking out the orderrelated noise and high frequency components of the time averaged signalto enhance the amplitude envelope; and display means for displaying theenhanced signal to pinpoint the location of the excessively vibratingblade and indicate its relative vibration amplitude.
 9. An apparatus fordetecting and identifying an excessively vibrating blade of the rotatingportion of a turbomachine by analysis of the characteristic Dopplerwaveform resulting from the vibrating blade comprising:sensor meansdisposed at a fixed location proximate the rotating portion of theturbomachine for sensing the acoustical energy and generating acomposite electrical signal in response thereto; time averaging meansfor synchronous time averaging the detected composite signal to removerandom noise and undesirable non-order related components therefrom;blanking means for blanking out the order related noise components ofthe time averaged signal; envelope detecting means for detecting theblanked time averaged signal and for blanking out the high frequencyportion thereof to enhance the amplitude envelope; and display means fordisplaying the enhanced signal to pinpoint the location of theexcessively vibrating blade and indicate its relative vibrationamplitude.